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dc.contributor.authorWang, Haidongen_US
dc.date.accessioned2009-09-16T18:19:52Z
dc.date.available2009-09-16T18:19:52Z
dc.date.issued2009-09-16T18:19:52Z
dc.date.submittedJanuary 2008en_US
dc.identifier.otherDISS-10044en_US
dc.identifier.urihttp://hdl.handle.net/10106/1793
dc.description.abstractIn this thesis, we propose minimum-effort driven navigational techniques for enterprise database systems based on the faceted search paradigm. Our proposed techniques dynamically suggest facets for drilling down into the database such that the cost of navigation is minimized. At every step, the system asks the user a question or a set of questions on different facets and depending on the user response, dynamically fetches the next most promising set of facets, and the process repeats. Facets are selected based on their ability to rapidly drill down to the most promising tuples, as well as on the ability of the user to provide desired values for them. Our facet selection algorithms also work in conjunction with any ranked retrieval model where a ranking function imposes a bias over the user preferences for the selected tuples. Our methods are principled as well as efficient, and our experimental study validates their effectiveness on several application scenarios.en_US
dc.description.sponsorshipDas, Gautamen_US
dc.language.isoENen_US
dc.publisherComputer Science & Engineeringen_US
dc.titleDynacet: A Minimum-effort Driven Dynamic Faceted Search System Over Structured Databasesen_US
dc.typeM.S.en_US
dc.contributor.committeeChairDas, Gautamen_US
dc.degree.departmentComputer Science & Engineeringen_US
dc.degree.disciplineComputer Science & Engineeringen_US
dc.degree.grantorUniversity of Texas at Arlingtonen_US
dc.degree.levelmastersen_US
dc.degree.nameM.S.en_US
dc.identifier.externalLinkhttp://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=178
dc.identifier.externalLinkDescriptionLink to Research Profiles


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